Koichi Takayama
- Oncology top 0.5%
- Lung Cancer Research Studies 84
- Cancer Immunotherapy and Biomarkers 39
- Immunology top 0.5%
- Pulmonary and Respiratory Medicine top 0.5%
- Lung Cancer Treatments and Mutations 113
- Lung Cancer Diagnosis and Treatment 36
- Microbiology top 0.5%
- Cancer Research top 1%
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- Computational Fluid Dynamics and Aerodynamics 31
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- Virus-based gene therapy research 30
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- Cancer Research and Treatments 29
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- Combustion and Detonation Processes 27
- Co-authors
- N QureshiYoichi NakanishiE. RibiChikako KiyoharaNobuyuki HaraJ O KilburnPaolo MascagniJunji Uchino
- Journals
- Proceedings of the National Academy of Sciences (2 papers)Journal of Biological Chemistry (20 papers)Journal of Clinical Oncology (6 papers)
- Partner nations
- JapanUnited StatesAustralia
In The Last Decade
Koichi Takayama
517 papers receiving 13.9k citations
Hit Papers
Peers
Comparison fields: 5 of 190
- Oncology 4.5k
- Immunology 2.9k
- Pulmonary and Respiratory Medicine 3.0k
- Microbiology 508
- Cancer Research 1.1k
Countries citing papers authored by Koichi Takayama
This map shows the geographic impact of Koichi Takayama's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Koichi Takayama with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Koichi Takayama more than expected).
Fields of papers citing papers by Koichi Takayama
This network shows the impact of papers produced by Koichi Takayama. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Koichi Takayama. The network helps show where Koichi Takayama may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Koichi Takayama, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 9 | |
| 2 | 2023 | 20 | |
| 3 | 2023 | 5 | |
| 4 | 2023 | 5 | |
| 5 | 2023 | 1 | |
| 6 | 2023 | 7 | |
| 7 | 2023 | 5 | |
| 8 | 2023 | 4 | |
| 9 | 2023 | 5 | |
| 10 | 2023 | 3 | |
| 11 | 2023 | 7 | |
| 12 | 2021 | 33 | |
| 13 | 2021 | 1 | |
| 14 | 2020 | 20 | |
| 15 | 2019 | 78 | |
| 16 | Induction of PD-L1 Expression by the EML4–ALK Oncoprotein and Downstream Signaling Pathways in Non–Small Cell Lung Cancerbreakdown → | 2015 | 366 |
| 17 | 2014 | 15 | |
| 18 | 2012 | 188 | |
| 19 | 2005 | 6 | |
| 20 | 1996 | 68 |
About Koichi Takayama
Koichi Takayama is a scholar working on Oncology, Pulmonary and Respiratory Medicine and Biotechnology, having authored 542 papers that have together received 14.4k indexed citations. Recurring topics across this work include Lung Cancer Treatments and Mutations (113 papers), Lung Cancer Research Studies (84 papers), Cancer Immunotherapy and Biomarkers (39 papers), Lung Cancer Diagnosis and Treatment (36 papers), Computational Fluid Dynamics and Aerodynamics (31 papers), Virus-based gene therapy research (30 papers), Cancer Research and Treatments (29 papers) and Combustion and Detonation Processes (27 papers). The work is most often cited by research in Oncology (4.5k citations), Immunology (2.9k citations) and Pulmonary and Respiratory Medicine (3.0k citations). Koichi Takayama has collaborated with scholars based in Japan, United States and Australia. Frequent co-authors include N Qureshi, Yoichi Nakanishi, E. Ribi, Chikako Kiyohara, Nobuyuki Hara, J O Kilburn, Paolo Mascagni, Junji Uchino, Taishi Harada and Tadaaki Yamada. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Journal of Clinical Oncology.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.